Why traditional Marketing Attribution doesn't work anymore

Marketing Attribution as a measurement strategy has existed for many decades, dating all the way back to the early days of advertising and the beginnings of the internet. The early days of marketing attribution primarily used simple models such as first-click and last-click. These models assigned 100% credit to either the first or last touchpoint in a customer's journey, but did not take into account the other touchpoints in between. These models still exist to a certain extent today, especially last-click attribution models are based on the initial concepts.

However, with the development of the internet as well as the rise of digital marketing and the vast availability of data, attribution models progressed into what we see today, namely Multi-Touch Attribution (MTA) models enhanced by machine learning.

Thanks to the of the rise of digital channels and tools such as cookies, tracking pixels, and analytics software, it became possible to track customer journeys and assign conversion credit to specific touchpoints. The development of these more advanced attribution models began in the late 1990s and early 2000s and has continued to evolve with the growth of technology today.

This article will walk you through a brief history of attribution models while diving into current events and analyzing the place attribution models have in today's competitive and complicated digital marketing space.

How did all start?

Well, if we want to go all the way back in time, then we can start by saying that Marketing Mix Modeling and Marketing Attribution Models had somewhat a common past. Both originating back in the 1950s. In the following decades of the 20th century both measurement models became increasingly popular as companies sought to better understand the impact of their marketing efforts. These models have continued to evolve and become more sophisticated as technology and data have become more prevalent.

During the early 1990s, the internet became more popular and available, which triggered a new era of possibilities in terms of e-commerce and digital marketing. However, in the early days of the internet, regulation was relatively minimal. We could say that similarly to the Western expansion, the digital marketing landscape in the 1990s was pretty much the equivalent of the wild west. The internet was in its infancy and the world of digital marketing was still very new and untested. Consumers were interacting with digital content and advertising in ways that were different from traditional media, and marketers were faced with the challenge of understanding this new behavior and making sense of the data that was becoming available.

At the same time, with the rise of digital marketing marketers were presented with new opportunities in terms of reaching and engaging with consumers in a more personalized and targeted way. The internet was new and flashy, and the consumers clicked and visited things quite spontaneously. Detailed data on individual consumers became easily available and it allowed marketers to tailor their advertising messages to specific consumer segments. Consumers started receiving personalized ads which most likely was a new and exciting development in the 1990s. With the availability of detailed data on individual consumers, marketers were able to create more targeted and relevant advertising messages, which was a stark contrast to the more generic advertising messages that were prevalent in the media back then.

It must have felt amazing right? Finally receiving ads for things that interest you instead of reading everything in newspapers or receiving thick catalogues over mail. The ability to receive ads that were specifically tailored to the customers‘ interests and preferences was likely seen as a major improvement over the generic ads they were used to seeing. However, while personalized advertising was a positive development for many consumers in the 1990s, it also raised privacy concerns as people became more aware of the amount of data that was being collected about them. This remained a persistent concern in the world of digital marketing, and led to increased regulation and scrutiny of data collection and use practices in recent years.

How can attribution models navigate today’s digital marketing space?

Traditional Marketing Attribution models, such as first-click and last-click, are becoming less effective in today's digital landscape due to the changing nature of consumer behavior and the increasing complexity of the digital marketing ecosystem.

Why?

• today consumers interact with brands across multiple devices and channels, making it difficult to attribute their behavior to a single touchpoint or channel
• traditional attribution models rely on limited data and do not take into account the full customer journey or the impact of other touchpoints
• increased awareness related to data privacy
• hyper-targeting
• overemphasis on short-term conversions

Let’s dive into more details!

Traditional Attribution models have been replaced by more sophisticated models, such as Multi-Touch Attribution (MTA) models or Marketing Mix Modeling (MMM) which are better equipped to handle the complexities of the modern digital marketing landscape. MTA evolved to encompass a wide range of methods, models, and techniques for measuring and analyzing the impact of marketing efforts across multiple channels and touchpoints. Read more about MMM vs MTA here .

That being said, traditional marketing attribution models may still have some limited use in certain situations for now, such as when data is limited or when a simpler attribution model is preferred. However, for most businesses, it is recommended to use more advanced marketing measurement solutions in order to get a more accurate understanding of the impact of their marketing efforts.

One crucial factor that contributed to the downfall of marketing attribution models is the over-reliance of marketers on these solutions which has led to hyper-targeting and an overemphasis on short-term conversions.

Essentially, Hyper-targeting is the practice of targeting ads to very specific customer segments based on dats such as: demographics, interests, behaviors, and other characteristics. The goal of hyper-targeting is to deliver highly relevant and personalized messages to consumers, with the hope of improving conversion rates.

However, this can result in an overemphasis on short-term conversions because by focusing solely on converting individual customers in the short-term, marketers may neglect the long-term impact of their advertising efforts. This can lead to a narrow and unsustainable growth strategy, where conversions are driven by aggressive discounting and other short-term incentives, rather than by building strong relationships and brand loyalty.

Therefore, nowadays, we encounter the feeling of saturation in terms of digital media because present day consumers are less and less interested in the constant ads showers. Targeted ads became less effective as people began using ad-blockers to keep their data private. People also became more aware of their privacy and how their personal information was being used, leading to strong opposition to these practices.

Today in the digital age, MTA is more critical, as organizations face increasing challenges in understanding and managing the customer journey across multiple channels and touchpoints. However, MTA is still heavily dependent on the collection and analysis of data, especially data related to consumer interactions with marketing messages. This data is often collected through the use of third party cookies.

What about cookies?

Cookies have been a critical tool for digital marketers in their efforts to understand consumer behavior and optimize their marketing performance, but they have also been a source of controversy and concern related to data privacy and security.

In order to address the consumer’s privacy concerns, several data privacy regulations have been adopted around the world such as the European Union's General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

What are the implications for organizations?

• they must comply with regulations and take steps to protect consumer privacy by obtaining consent for data collection
• they must be transparent about the data collected
• they must implement robust security measures to protect consumer data

These regulations can pose significant challenges for MTA solutions since they limit the amount and type of data that they can be collected and use for attribution purposes.

What will the future of marketing measurement look like?

We believe that the future of marketing measurement is likely to be defined by increased measurement accuracy, data transparency, and corporate accountability. The future of cookieless marketing measurement will be driven by a growing focus on privacy, security, and the use of compliant technologies.

It's time to look at the bigger picture. We're living at times of great uncertainty, and the role of marketing is to build relationships and trust between brands and consumers.

The future requires a more holistic approach to marketing measurement and attribution, which goes beyond simply tracking short-term conversions.

Organizations must be willing to:

• focus on understanding the full customer journey
• understanding the impact of brand building efforts on long-term loyalty and advocacy
• be aware of the impact that their marketing spend has on the sales target because the consumers become more and more aware of marketing tactics

This can be achieved through the integration of various data sources, including both offline and online data, and the use of advanced analytical techniques such as MTA combined with MMM and lift tests for an encompassing marketing strategy. Lift tests help marketing measurement accuracy by providing a way to measure the impact of different marketing touchpoints on conversion rates. You can read more about MMM and Lift tests here .

Most likely in the future the use of MTA as a sole marketing measurement solution will decline. This is not only driven by the privacy restrictions placed on third-party cookies, but also by a broader shift in consumer preferences and attitudes towards marketing practices. Consumers are increasingly aware of how their personal data is being used, and are demanding greater transparency and control over their information. As a result, marketers must adapt to be more creative and customer-centric in their approach to marketing, rather than relying solely on data-driven targeting and optimization. Therefore, we recommend a combined marketing strategy in the future that utilizes MTA but also MMM and lift tests in order to accurately understand the impact of marketing efforts both in the short and long term.

Despite the potential for cookies to remain in use to a certain extent or for alternative tracking methods such as server-side tracking to emerge, it may not be a wise decision for marketers to continue relying on marketing attribution models that are based on the collection of consumer data. Since consumers became more aware of privacy issues and increasingly concerned about the use of their personal information, there is a growing sentiment against data-driven marketing practices. Therefore, the expectations for marketers to be more transparent and respectful of their customers' privacy should be highly regarded in the future marketing strategy planning.

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